This paper deals with the errors and uncertainties in skyglow measurements caused by the variation of sky's spectrum. It considers the theoretical spectral response of common instruments that are used for light pollution assessment. Various types of light sources were used in this investigation. This study calculates the spectral mismatch errors and the corresponding correction factors for each combination of instrument and light source. The calculation method is described and the results are presented in multiple figures. Calculated data show a big variation in potential errors that can be introduced when comparing readings of diverse instruments without considering the sky spectrum variation. This makes the spectral data of the sky a mandatory input to the dark sky assessment. Useful conclusions, related to instruments with better or worse behaviour, are derived from the calculations. The paper also includes suggestions on how to conduct multi-instrument measurements with or without spectral data.

The human ocular system functions in a dual manner. While the most well-known function is to facilitate vision, a growing body of research demonstrates its role in resetting the internal body clock to synchronize with the 24-hour daily cycle. Most research on circadian rhythms is performed in controlled laboratory environments. Little is known about the variability of circadian light within the built and natural environments. Currently, very few specialized devices measure the circadian light, and they are not accessible to many researchers and practitioners. In this paper, tristimulus colour calibration procedures for high dynamic range photography are developed to measure circadian lighting. Camera colour accuracy is evaluated through CIE trichromatic (XYZ) measurements; and the results demonstrate a strong linear relationship between the camera recordings and a scientific-grade colorimeter. Therefore, it is possible to correct for the colour aberrations and use high dynamic range photographs to measure both photopic and circadian lighting values. Spectrophotometric measurements are collected to validate the methodology. Results demonstrate that measurements from high dynamic range photographs can correspond to the physical quantity of circadian luminance with reasonable precision and repeatability. Circadian data collected in built environments can be utilized to study the impact of design decisions on human circadian entrainment and to create guidelines and metrics for designing circadian friendly environments.

The successful launch of Luojia 1-01 complements the existing nighttime light data with a high spatial resolution of 130 m. This paper is the first study to assess the potential of using Luojia 1-01 nighttime light imagery for investigating artificial light pollution. Eight Luojia 1-01 images were selected to conduct geometric correction. Then, the ability of Luojia 1-01 to detect artificial light pollution was assessed from three aspects, including the comparison between Luojia 1-01 and the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS), the source of artificial light pollution and the patterns of urban light pollution. Moreover, the advantages and limitations of Luojia 1-01 were discussed. The results showed the following: (1) Luojia 1-01 can detect a higher dynamic range and capture the finer spatial details of artificial nighttime light. (2) The averages of the artificial light brightness were different between various land use types. The brightness of the artificial light pollution of airports, streets, and commercial services is high, while dark areas include farmland and rivers. (3) The light pollution patterns of four cities decreased away from the urban core and the total light pollution is highly related to the economic development. Our findings confirm that Luojia 1-01 can be effectively used to investigate artificial light pollution. Some limitations of Luojia 1-01, including its spectral range, radiometric calibration and the effects of clouds and moonlight, should be researched in future studies.

Big lighting data are required for evaluation of lighting performance and impacts on human beings, environment, and ecology for smart urban lighting. However, traditional approaches of measuring road lighting cannot achieve this aim. We propose a rule-of-thumb model approach based on some feature points to reconstruct road lighting in urban areas. We validated the reconstructed illuminance with both software simulated and real road lighting scenes, and the average error is between 6 and 19%. This precision is acceptable in practical applications. Using this approach, we reconstructed the illuminance of three real road lighting environments in a block and further estimated the mesopic luminance and melanopic illuminance performance. In the future, by virtue of Geographic Information System technology, the approach may provide big lighting data for evaluation and analysis, and help build smarter urban lighting.

Luojia 1-01 satellite, launched on 2 June 2018, provides a new data source of nighttime light at 130 m resolution and shows potential for mapping urban extent. In this paper, using Luojia 1-01 and VIIRS nighttime light imagery, we compared several methods for extracting urban areas, including Human Settlement Index (HSI), Simple Thresholding Segmentation (STS) and SVM supervised classification. According to the accuracy assessment, the HSI method using LJ1-01 data had the best performance in urban extent extraction, which presented the largest Kappa Coefficient value, 0.834, among all the results. For the urban areas extracted by VIIRS based HSI method, the largest Kappa Coefficient value was 0.772. In contrast, the largest Kappa Coefficient values obtained by STS method were 0.79 and 0.7512 respectively when using LJ1-01 and VIIRS data, while for SVM method the values were 0.7829 and 0.7486 when using Landsat-LJ and Landsat-VIIRS composite data respectively. The experimented results demonstrated that the utilization of nighttime light imagery can largely improve the accuracy of urban extent extraction and LJ1-01 data, with a higher resolution and more abundant spatial information, can lead to better identification results than its predecessors.